Research on strategy for optimizing coverage of WSNs based on multi-particle PSO

In order to improve the network performance and increase network coverage rate,the present research proposed a wireless sensor networks(WSNs) coverage optimization strategy on the basis of the evolution of multi-particle particle swarm optimization(MPSO).By adopting a number of particles independently searching for solutions space,the strategy improved the optimization of the algorithm ability and thus effectively avoid the premature so that the stability of the algorithm was improved.The simulation shows,compared with elementary particle swarm optimization(PSO),the conventional genetic algorithms(CGA) and quantum of the new genetic algorithm(NQGA) interms of the optimization effectiveness,that the coverage rate increased by 8.39%,3.07% and 0.75% and convergence rate increased 25.3% and 23.8%.Therefore,the MPSO strategy has a better coverage optimization results than PSO,CGA and NQGA.